Surveillance Systems

In the 2015 dengue outbreak in Taiwan, 43,784 people were infected and 228 died, making it the nation’s largest outbreak ever. Facing the increasing threat of dengue, the integration of health information for prevention and control of outbreaks becomes very important. Based on past epidemics, the areas with higher incidence of dengue fever are located in southern Taiwan. Without a smart and integrated surveillance system, the information on case distribution, high risk areas, mosquito surveillance, flooding areas and so on is fragmented. The first-line public health workers need to check all this information through different systems manually. When outbreaks occurred, paper-based outbreak investigation forms had to be prepared and filled in by public health workers. Then, they needed to enter part of this information into Taiwan CDC’s system. Duplicated work occurred and cost lots of labor time during the epidemic period. Therefore, we choose one rural county, Pingtung County, with scarce financial resources, to set up a new dengue surveillance system.

Objective:

In this paper we designed one cross-platform surveillance system to assist dengue fever surveillance, outbreak investigation and risk management of dengue fever.

Public Health England's syndromic surveillance service monitor presentations for gastrointestinal illness to detect increases in health care seeking behaviour driven by infectious gastrointestinal disease. We use regression models to create baselines for expected activity and then identify any periods of signficant increases. The introduction of a rotavirus vaccine in England during July 2013 (Bawa, Z. et al. 2015) led to a reduction in incidence of the disease, requiring a readjustment of baselines.

Objective:

To adjust modelled baselines used for syndromic surveillance to account for public health interventions. Specifically to account for a change in the seasonality of diarrhoea and vomiting indicators following the introduction of a rotavirus vaccine in England.

Ministries of Health in Low and Middle Income Countries (LMIC) are making or trying to make public health decisions for infectious disease conditions like HIV using data garnered from sentinel events and disease tracking in the community. The process of gathering and aggregating data for these case-based reports for is, in all too often a cumbersome or paper-based process. The Center for Disease Control (CDC) was interested in prototyping and piloting approaches that could improve the efficiency and reliability of case reports in resource-constrained environments. One of their primary goals was to demonstrate how electronic data gathered in the front lines of care could be leveraged to automate and improve the reliability of data within case reports driving public health decisions at regional and country levels. OpenMRS is an open source medical record system platform often used in resource constrained environments. Since OpenMRS is used as an electronic medical record system in several African countries and has been connected to regional or country-level health exchanges, the CDC was interested in building a working solution for electronic case based reporting using OpenMRS and a health information exchange.

Objective:

We demonstrate an architecture for driving regional public health decisions with automated and semi-automated data collected from open source point of care systems in resource constrained environments.

Early Notification Detection Systems have taken a critical role in providing early notice of disease outbreaks. To improve the detection methods for disease outbreaks, many detection methods have been created and implemented. However, there is limited information on the effectively of syndromic surveillance in Thailand. Knowing the performance, strengths and weakness of these surveillance systems in providing early warning for outbreaks will increase disease outbreak detection capacity in Thailand.

Objective:

This paper presents an investigation using early notification methods to enhancing epidemic detection in syndromic surveillance data from royal Thai army in Thailand.

The use of social media as a syndromic sentinel for diseases is an emerging field of growing relevance as the public begins to share more online, particularly in the area of influenza. Several applications have been developed to predict or monitor influenza activity using publicly posted or self-reported online data; however, few have prioritized accuracy at the local level. In 2016, the Cook County Department of Public Health (CCDPH) collected localized Twitter information to evaluate its utility as a potential influenza sentinel data source. Tweets from MMWR week 40 through MMWR week 20 indicating influenza-like illness (ILI) in our jurisdiction were collected and analyzed for correlation with traditional surveillance indicators. Social media has the potential to join other sentinels, such as emergency room and outpatient provider data, to create a more accurate and complete picture of influenza in Cook County.

Objective:

To determine if social media data can be used as a surveillance tool for influenza at the local level.

In 2005, the Cook County Department of Public Health (CCDPH) began using the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) as an emergency department (ED)-based local syndromic surveillance program (LSSP); 23 (100%) of 23 hospitals in suburban Cook County report to the LSSP. Data are transmitted in delimited ASCII text files (i.e., flat files) and contain a unique patient identifier, visit date and time, zip code, age, sex, and chief complaint. Discharge diagnosis and disposition are optional data elements. Prior to 2017, the Illinois Department of Public Health placed facilities participating in the Cook LSSP in a holding queue to transform their flat file submissions into a HL7 compliant message; however as of 2017, eligible hospitals must submit HL7 formatted production data to IDPH to fulfill Meaningful Use. The primary syndromic surveillance system for Illinois is the National Syndromic Surveillance Program (NSSP), which transitioned to an ESSENCE interface in 2016. As of December 2016, 20 (87%) of 23 hospitals reporting to the LSSP also reported to IDPH and the NSSP. As both syndromic surveillance systems aim to collect the same data, and now can be analyzed with the same interface, CCDPH sought to compare the LSSP and NSSP for data completeness, consistency, and other attributes.

Objective:

This analysis was undertaken to determine how the data completeness, consistency, and other attributes of our local syndromic surveillance program compared to the National Syndromic Surveillance Platform.

The New York City Department of Health and Mental Hygiene’s (NYC DOHMH) Division of Disease Control (DDC) conducts surveillance of more than 90 specific diseases and conditions and relies on both provider reports and electronic laboratory reports for data. While laboratory reports provide vital laboratory data and represent the majority of the surveillance data that DOHMH receives, they are not always timely or sufficient to confirm a case. Provider reports, in contrast, contain data often not available in laboratory reports and can be more prompt than laboratory reports. Health care providers submit provider reports through multiple channels, including through mailing or faxing paper forms, phone calls, and Reporting Central (RC). In 2016, providers used RC to submit ~51,000 provider reports.

Objective:

As part of New York City Department of Health and Mental Hygiene’s (NYC DOHMH) efforts to improve provider reporting, the Division of Disease Control surveyed and conducted focus groups with users of a web-based reporting portal called Reporting Central (RC) to learn about their experience with submitting provider reports through RC and the impact of their experience on data submission.

The current surveillance system for opioid-related overdoses at UDOH has been limited to mortality data provided by the Office of the Medical Examiner (OME). Timeliness is a major concern with OME data due to the considerable lag in its availability, often up to six months or more. To enhance opioid overdose surveillance, UDOH has implemented additional surveillance using timely syndromic data to monitor fatal and nonfatal opioid-related overdoses in Utah.

Objective:

To monitor opioid-related overdose in real-time using emergency department visit data and to develop an opioid overdose surveillance report for Utah Department of Health (UDOH) and its public health partners.

Infectious diseases can spread across borders. The Arizona Department of Health Services (ADHS) collects information on binational infectious disease cases and shares it with Mexico. Infectious disease investigation in Arizona is enhanced by using an electronic surveillance platform known as the Medical Electronic Disease Surveillance Intelligence System (MEDSIS), and in 2010 a specific variable for binational cases with Mexico was added to the platform. ADHS also maintains a binational case definition in the state reportable communicable morbidities manual. Arizona partners with the US Centers for Disease Control and Prevention (CDC)’s Division of Global Migration and Quarantine (DGMQ), US Mexico Unit (USMU), in a monthly binational case reporting project, and shares information with the Ministry of Health of the State of Sonora, Mexico, (SON MOH) to reinforce ongoing communication, to establish baseline disease patterns, and to help detect binational outbreaks. In 2007, the Ministry of Health of the State of Sonora began to use the MEDSIS system for real-time secure case notification, and secure file sharing, using the Arizona’s Health Services Portal and secure e-mail accounts for confidential communication between both states.

Objective:

To describe 5 years of binational infectious disease surveillance using the binational variable in the medical electronic surveillance system in Arizona.

While UC does not have a standard definition, it can generally be described as the delivery of ambulatory medical care outside of a hospital emergency department (ED) on a walk-in basis, without a scheduled appointment, available at extended hours, and providing an array of services comparable to typical primary care offices. UC facilities represent a growing sector of the United States healthcare industry, doubling in size between 2008 and 2011. The Urgent Care Association of America (UCAOA) estimates that UC facilities had 160 million patient encounters in 2013. This compares to 130.4 million patient encounters in EDs in 2013, as reported by the National Hospital Ambulatory Medical Care Survey. Public Health (PH) is actively working to broaden syndromic surveillance to include urgent care data as more individuals use these services. PH needs justification when reaching out to healthcare partners to get buy-in for collecting and reporting UC data.

Objective:

Provide justification for the collection and reporting of urgent care (UC) data for public health syndromic surveillance.